Video watermarking using neural networks

Latha, S. Bhargavi; Reddy, D.V. Krishna; Damodaram, A.

doi:10.1504/ijics.2021.112207

Cited by 3 publications

(2 citation statements)

References 34 publications

(42 reference statements)

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“…Video watermarking can be divided into original video watermarking algorithm and video watermarking algorithm based on compression domain. e former can refer to the existing image watermarking algorithm [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Audio and Video Matching Zero‐Watermarking Algorithm Based on NSCT

et al. 2022

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In the Internet age, information security is threatened anytime and anywhere and the copyright protection of audio and video as well as the need for matching detection is increasingly strong. In view of this need, this paper proposes a zero-watermarking algorithm for audio and video matching based on NSCT. The algorithm uses NSCT, DCT, SVD, and Schur decomposition to extract video features and audio features and generates zero-watermark stream through synthesis, which is stored in a third-party organization for detection and identification. The detection algorithm can obtain zero watermark from the audio and video to be tested and judge and locate tampering by comparing with the zero watermark of the third party. From the experimental results, this algorithm can not only detect whether the audio and video are mismatched due to tampering attacks but also locate the mismatched audio and video segments and protect the copyright.

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Section: Introductionmentioning

confidence: 99%

Audio and Video Matching Zero‐Watermarking Algorithm Based on NSCT

et al. 2022

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“…Security: the main indicator of securing digital objects from hackers, embedded information is tamper-proof [11].  Capacity: The measure of embedded data should be huge enough to extraordinarily recognize the proprietorship of the video [12].…”

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confidence: 99%

Survey of Recent Video Watermarking Techniques

Hummad¹,

Hassan²

2021

ETJ

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With the development of the Internet coupled with expanding the accessibility of multimedia, various copyright issues have resulted. Several researchers have been working on watermarks to provide the security, durability, and a perception of multimedia. This paper a review of some recent works is presented related to video watermarking techniques, this study focuses on the pros and cons of recent video watermarking, areas of application, and the different types and attacks that are standing against these watermarking techniques. The results obtained from this study showed that watermark techniques based on the transfer domain, are more popular than those of the spatial domain.

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Zero-watermarking Algorithm for Audio and Video Matching Verification

Sun¹,

Zhao²,

Zhang³

et al. 2022

MATH

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<abstract> <p>For the needs of tamper-proof detection and copyright identification of audio and video matching, this paper proposes a zero-watermark algorithm that can be used for audio and video matching verification. The algorithm segments audio and video in smaller time units, generates a video frame feature matrix based on NSCT, DCT, and SVD, and generates a sound watermark based on methods such as DWT and K-means. The zero watermark combines video, audio and copyright information. The experimental results show that the zero watermark generated by this algorithm can not only realize highly accurate matching detection and positioning of audio and video, but also well resist common single attack and combination attacks such as noise, scaling, rotation, frame attack and format conversion, which has good robustness.</p> </abstract>

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Video watermarking using neural networks

Cited by 3 publications

References 34 publications

Audio and Video Matching Zero‐Watermarking Algorithm Based on NSCT

Audio and Video Matching Zero‐Watermarking Algorithm Based on NSCT

Survey of Recent Video Watermarking Techniques

Zero-watermarking Algorithm for Audio and Video Matching Verification

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